Our objective is to provide accurate, objective, bedside measurements of left ventricular performance from 2D echocardiograms. Up to this point in time, such quantitation of 2D echocardiograms has been achieved by either manual or computer based detection of the endocardial and epicardial borders. These methods are time-consuming, but more importantly variable, since borders must be drawn through individual spots in the image representing specular targets which may be present in one image and absent in another. In this proposal a fundamentally different method is developed which considers the image as the 2-dimensional plot of the position of specular targets in a pie-shaped sample volume. The motion pattern of these spots is used to quantify regional wall motion and wall thickening. To accomplish this, spots with high probability of being specular targets are retained and reduced to single points. The center point of the ventricle is marked and the ventricle is divided into equal 45 degree octants. Histograms are then constructed in each octant which represents the number of points (specular targets) at a given distance from the center point. By means of cross correlation and histogram stretching, the patterns of the histograms from sequential frames during a cardiac cycle can be followed. Thus, the problem of image processing in 2D echo images is transformed to a problem in pattern recognition in radial frequency histograms. Global chamber area and global muscle area can be estimated by curve fitting through the histogram peaks on a frame. The research is designed to mathematically optimize this new method with the following specific aims: a) increase the accuracy of measurements made from 2D echos, b) use histogram entropy to develop a figure of merit for the measurements obtained, c) use the histograms as a means of automatic registration for frame averaging and increased patient yield, and d) provide the regional functional measurements at the bedside. Accuracy will be evaluated as the sensitivity and specificity of the algorithm to detect change in stroke volume in the open chest dog preparation instrumented with an aortic electromagnetic flow meter and myocardial thickness sonomicrometers. Sensitivity and specificity to change will also be evaluated in the catheterization laboratory against change in stroke volume induced by afterload reduction and measured by the electromagnetic flow catheter and green dye cardiac output.